Combining eigenvector methods and support vector machines for detecting variability of Doppler ultrasound signals

Computer Methods and Programs in Biomedicine

Volumn 86, Issue 2, 2007, Pages 181-190

  Übeyli, Elif Derya ^a  

^a TOBB UNIVERSITY OF ECONOMICS AND TECHNOLOGY   (Turkey)

Author keywords

Doppler ultrasound signals; Eigenvector methods; Multiclass support vector machine (SVM)

Indexed keywords

DOPPLER EFFECT; EIGENVALUES AND EIGENFUNCTIONS; ERROR CORRECTION; PATTERN RECOGNITION; SUPPORT VECTOR MACHINES; ULTRASONIC MEASUREMENT;

BEHCET DISEASES; DOPPLER ULTRASOUND SIGNALS; INTERNAL CAROTID ARTERIAL (ICA); OPHTHALMIC ARTERIAL (OA);

SIGNAL DETECTION;

ACCURACY; ADULT; AGED; ANALYTICAL ERROR; ARTERY OCCLUSION; ARTICLE; BEHCET DISEASE; CAROTID ARTERY OBSTRUCTION; CONTROLLED STUDY; DOPPLER FLOWMETRY; FEMALE; HUMAN; INTERNAL CAROTID ARTERY; MAJOR CLINICAL STUDY; MALE; MATHEMATICAL COMPUTING; OPHTHALMIC ARTERY; RECORDING; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE; TECHNIQUE;

ADULT; AGED; ALGORITHMS; CAROTID ARTERY DISEASES; FEMALE; HUMANS; MALE; MIDDLE AGED; SIGNAL PROCESSING, COMPUTER-ASSISTED; TURKEY; ULTRASONOGRAPHY, DOPPLER;

EID: 34047247923     PISSN: 01692607     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cmpb.2007.01.006     Document Type: Article

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